Seasonal Synchronization of Influenza in the United States Older Adult Population

In temperate regions, influenza epidemics occur annually with the highest activity occurring during the winter months. While seasonal dynamics of the influenza virus, such as time of onset and circulating strains, are well documented by the Centers for Disease Control and Prevention Influenza Surveillance System, an accurate prediction of timing, magnitude, and composition of circulating strains of seasonal influenza remains elusive. To facilitate public health preparedness for seasonal influenza and to obtain better insights into the spatiotemporal behavior of emerging strains, it is important to develop measurable characteristics of seasonal oscillation and to quantify the relationships between those parameters on a spatial scale. The objectives of our research were to examine the seasonality of influenza on a national and state level as well as the relationship between peak timing and intensity of influenza in the United States older adult population.A total of 248,889 hospitalization records were extracted from the Centers for Medicare and Medicaid Services for the influenza seasons 1991-2004. Harmonic regression models were used to quantify the peak timing and absolute intensity for each of the 48 contiguous states and Washington, DC. We found that individual influenza seasons showed spatial synchrony with consistent late or early timing occurring across all 48 states during each influenza season in comparison to the overall average. On a national level, seasons that had an earlier peak also had higher rates of influenza (r(s) = -0.5). We demonstrated a spatial trend in peak timing of influenza; western states such as Nevada, Utah, and California peaked earlier and New England States such as Rhode Island, Maine, and New Hampshire peaked later.Our findings suggest that a systematic description of influenza seasonal patterns is a valuable tool for disease surveillance and can facilitate strategies for prevention of severe disease in the vulnerable, older adult population

Interdisciplinary cooperation between dentists and endocrinologists for identification and management of diabetes mellitus

Background: DM mellitus (DM) leads to worsening periodontal diseases, and in turn the inflammatory diseases of maxillofacial region adversely affect the glycemic control and exacerbate the severity of DM, thereby engendering a vicious cycle that compromises the DM management in patients. Taking account of the bidirectional relationship between DM and periodontal disease, interdisciplinary examination of patients with both DM and periodontal diseases is warranted to improve the health outcomes in patients. Aims: This study aims to evaluate the perceptions of dentists and endocrinologists on the interdisciplinary cooperation for identification and management of patients with DM. Materials and methods: Studying patients’ knowledge about DM and their compliance in providing endocrinological recommendations, dental screening survey to identify DM’ risk and signs The research was done in 2015-2016 years using clinical survey (dental status survey), statistical analysis. 432 patients from different dental organizations and 433 doctors (371 – dentists and 62 – endocrinologists) took part in the research. The research was approved by Regional research ethics committee. The written informed consent was taken from each participant. Results: There was insufficient interdisciplinary collaboration for identification and management of patients with diabetes, and lack of motivation among dental patients to endocrinological survey. Hence, it is important to incorporate definitive screening for risk of DM for patients with inflammatory periodontal disease and include dentists in consultation for patients with DM. The feasibility of statutory determination of collaboration between specialists in identification and management of patients with DM was found, dental lectures are necessary in DM school. Conclusions: Our findings suggest the necessity of including dentists in the standard of medical management of patients with DM and incorporating DM screening by a questionnaire upon dental examination

The effect of Helicobacter pylori infection on growth velocity in young children from poor urban communities in Ecuador

SummaryObjectiveTo characterize the potential effects of Helicobacter infections on growth velocity in low socioeconomic status young children in a developing country.MethodsChildren were recruited in poor suburbs of Quito, Ecuador. Normally nourished, mildly and substantially malnourished children (defined using weight-for-age Z-scores at recruitment) formed equal strata. Six height and weight measurements were collected during one year. Enrollment and exit serum samples were analyzed for anti-Helicobacter IgG and exit non-diarrheal feces tested for Helicobacter antigen.ResultsAmong 124 participants (enrollment age 19±9 months), 76 (61%) excreted fecal antigen at exit (were infected). Of these, 44 were seropositive at least once (chronic infections) and 32 tested seronegative both times (new or acute phase infections). The adjusted linear growth velocity during follow-up in children with new infections was reduced by 9.7 (3.8, 15.6) mm/year compared to uninfected controls and 6.4 (0.0, 12.9) mm/year compared to children with chronic infections. The effects of Helicobacter infections on ponderal growth were not significant.ConclusionThese results suggest that linear growth velocity is reduced in young children during the initial phase of Helicobacter infection

The use of remotely sensed environmental parameters for spatial and temporal schistosomiasis prediction across climate zones in Ghana

Schistosomiasis control in sub-Saharan Africa is enacted primarily through preventive chemotherapy. Predictive models can play an important role in filling knowledge gaps in the distribution of the disease and help guide the allocation of limited resources. Previous modeling approaches have used localized cross-sectional survey data and environmental data typically collected at a discrete point in time. In this analysis, 8 years (2008-2015) of monthly schistosomiasis cases reported into Ghana's national surveillance system were used to assess temporal and spatial relationships between disease rates and three remotely sensed environmental variables: land surface temperature (LST), normalized difference vegetation index (NDVI), and accumulated precipitation (AP). Furthermore, the analysis was stratified by three major and nine minor climate zones, defined using a new climate classification method. Results showed a downward trend in reported disease rates (~ 1% per month) for all climate zones. Seasonality was present in the north with two peaks (March and September), and in the middle of the country with a single peak (July). Lowest disease rates were observed in December/January across climate zones. Seasonal patterns in the environmental variables and their associations with reported schistosomiasis infection rates varied across climate zones. Precipitation consistently demonstrated a positive association with disease outcome, with a 1-cm increase in rainfall contributing a 0.3-1.6% increase in monthly reported schistosomiasis infection rates. Generally, surveillance of neglected tropical diseases (NTDs) in low-income countries continues to suffer from data quality issues. However, with systematic improvements, our approach demonstrates a way for health departments to use routine surveillance data in combination with publicly available remote sensing data to analyze disease patterns with wide geographic coverage and varying levels of spatial and temporal aggregation.Accepted manuscrip

L-Dopa and the Albino Riddle: Content of L-Dopa in the Developing Retina of Pigmented and Albino Mice

Background: The absence or deficiency of melanin as in albinos, has detrimental effects on retinal development that include aberrant axonal projections from eye to brain and impaired vision. In pigmented retinal pigment epithelium (RPE), dihydroxyphenalanine (L-Dopa), an intermediate in the synthetic path for melanin, has been hypothesized to regulate the tempo of neurogenesis. The time course of expression of retinal L-Dopa, whether it is harbored exclusively in the RPE, the extent of deficiency in albinos compared to isogenic controls, and whether L-Dopa can be restored if exogenously delivered to the albino have been unknown. Methodology/Principal Findings: L-Dopa and catecholamines including dopamine extracted from retinas of pigmented (C57BL/6J) and congenic albino (C57BL/6J-tyrc2j) mice, were measured throughout development beginning at E10.5 and at maturity. L-Dopa, but not dopamine nor any other catecholamine, appears in pigmented retina as soon as tyrosinase is expressed in RPE at E10.5. In pigmented retina, L-Dopa content increases throughout pre- and postnatal development until the end of the first postnatal month after which it declines sharply. This time course reflects the onset and completion of retinal development. L-Dopa is absent from embryonic albino retina and is greatly reduced in postnatal albino retina compared to pigmented retina. Dopamine is undetectable in both albino and pigmented retinas until after the postnatal expression of the neuronal enzyme tyrosine hydroxylase. If provided to pregnant albino mothers, L-Dopa accumulates in the RPE of the fetuses. Conclusions: L-Dopa in pigmented RPE is most abundant during development after which content declines. This L-Dopa is not converted to dopamine. L-Dopa is absent or at low levels in albino retina and can be restored to the RPE by administration in utero. These findings further implicate L-Dopa as a factor in the RPE that could influence development, and demonstrate that administration of L-Dopa could be a means to rescue developmental abnormalities characteristic of albinos

Seasonality of Rotavirus in South Asia: A Meta-Analysis Approach Assessing Associations with Temperature, Precipitation, and Vegetation Index

Rotavirus infection causes a significant proportion of diarrhea in infants and young children worldwide leading to dehydration, hospitalization, and in some cases death. Rotavirus infection represents a significant burden of disease in developing countries, such as those in South Asia.We conducted a meta-analysis to examine how patterns of rotavirus infection relate to temperature and precipitation in South Asia. Monthly rotavirus data were abstracted from 39 published epidemiological studies and related to monthly aggregated ambient temperature and cumulative precipitation for each study location using linear mixed-effects models. We also considered associations with vegetation index, gathered from remote sensing data. Finally, we assessed whether the relationship varied in tropical climates and humid mid-latitude climates.Overall, as well as in tropical and humid mid-latitude climates, low temperature and precipitation levels are significant predictors of an increased rate of rotaviral diarrhea. A 1°C decrease in monthly ambient temperature and a decrease of 10 mm in precipitation are associated with 1.3% and 0.3% increase above the annual level in rotavirus infections, respectively. When assessing lagged relationships, temperature and precipitation in the previous month remained significant predictors and the association with temperature was stronger in the tropical climate. The same association was seen for vegetation index; a seasonal decline of 0.1 units results in a 3.8% increase in rate of rotavirus.In South Asia the highest rate of rotavirus was seen in the colder, drier months. Meteorological characteristics can be used to better focus and target public health prevention programs

Age-Based Dynamics of a Stable Circulating Cd8 T Cell Repertoire Component

T-cell memory to pathogens can be envisioned as a receptor-based imprint of the pathogenic environment on the naive repertoire of clonotypes. Recurrent exposures to a pathogen inform and reinforce memory, leading to a mature state. The complexity and temporal stability of this system in man is only beginning to be adequately described. We have been using a rank-frequency approach for quantitative analysis of CD8 T cell repertoires. Rank acts as a proxy for previous expansion, and rank-frequency, the number of clonotypes at a particular rank, as a proxy for abundance, with the relation of the two estimating the diversity of the system. Previous analyses of circulating antigen-experienced cytotoxic CD8 T-cell repertoires from adults have shown a complex two-component clonotype distribution. Here we show this is also the case for circulating CD8 T cells expressing the BV19 receptor chain from five adult subjects. When the repertoire characteristic of clonotype stability is added to the analysis, an inverse correlation between clonotype rank frequency and stability is observed. Clonotypes making up the second distributional component are stable; indicating that the circulation can be a depot of selected clonotypes. Temporal repertoire dynamics was further examined for influenza-specific T cells from children, middle-aged, and older adults. Taken together, these analyses describe a dynamic process of system development and aging, with increasing distributional complexity, leading to a stable circulating component, followed by loss of both complexity and stability

Dynamic maps: a visual-analytic methodology for exploring spatio-temporal disease patterns

<p>Abstract</p> <p>Background</p> <p>Epidemiologic studies are often confounded by the human and environmental interactions that are complex and dynamic spatio-temporal processes. Hence, it is difficult to discover nuances in the data and generate pertinent hypotheses. Dynamic mapping, a method to simultaneously visualize temporal and spatial information, was introduced to elucidate such complexities. A conceptual framework for dynamic mapping regarding principles and implementation methods was proposed.</p> <p>Methods</p> <p>The spatio-temporal dynamics of <it>Salmonella </it>infections for 2002 in the U.S. elderly were depicted via dynamic mapping. Hospitalization records were obtained from the Centers of Medicare and Medicaid Services. To visualize the spatial relationship, hospitalization rates were computed and superimposed onto maps of environmental exposure factors including livestock densities and ambient temperatures. To visualize the temporal relationship, the resultant maps were composed into a movie.</p> <p>Results</p> <p>The dynamic maps revealed that the <it>Salmonella </it>infections peaked at specific spatio-temporal loci: more clusters were observed in the summer months and higher density of such clusters in the South. The peaks were reached when the average temperatures were greater than 83.4°F (28.6°C). Although the relationship of salmonellosis rates and occurrence of temperature anomalies was non-uniform, a strong synchronization was found between high broiler chicken sales and dense clusters of cases in the summer.</p> <p>Conclusions</p> <p>Dynamic mapping is a practical visual-analytic technique for public health practitioners and has an outstanding potential in providing insights into spatio-temporal processes such as revealing outbreak origins, percolation and travelling waves of the diseases, peak timing of seasonal outbreaks, and persistence of disease clusters.</p

Synthesis of novel hierarchical micro/nanostructures AlOOH/AlFe and their application for As(V) removal

Hierarchical micro/nanostructured composites, which contain iron and/or its (hydr)oxides, demonstrate high rate and capacity of arsenic adsorption. The main objective of this paper is the use of novel low toxicity AlOOH/AlFe hierarchical micro/nanostructures for arsenic removal. AlOOH/AlFe composite was obtained by simple water oxidation in mild conditions using AlFe bimetallic nanopowder as a precursor. AlFe bimetallic nanopowder was produced by electrical explosive of two twisted wires in argon atmosphere. The productivity of the electrical explosion assembly was 50 g/h, with the consumption of the electrical energy was 75 kW·h/kg. AlFe bimetallic nanoparticles were chemically active and interacted with water at 60 °C. This nanocomposite AlOOH/AlFe is low cost and adsorbs more than 200 mg/g As(V) from its aqueous solution. AlOOH/AlFe composite has flower-like morphology and specific surface area 247.1 m2/g. The phase composition of nanostructures is present AlOOH boehmite and AlFe intermetallic compound. AlOOH/AlFe composite was not previously used for this. The flower-shape AlOOH morphology not only facilitated deliverability, but increased the As(V) sorption capacity by up to 200 mg/g. The adsorption kinetics has been found to be described by a pseudo-second-order equation of Lagergren and Weber-Morris models while the experimental adsorption isotherm is closest to the Freundlich model. This indicates the energy heterogeneity of the adsorbent surface and multilayer adsorption. The use of non-toxic nanostructures opens up new options to treat water affected by arsenic pollution

Visual Analytics for Epidemiologists: Understanding the Interactions Between Age, Time, and Disease with Multi-Panel Graphs

Visual analytics, a technique aiding data analysis and decision making, is a novel tool that allows for a better understanding of the context of complex systems. Public health professionals can greatly benefit from this technique since context is integral in disease monitoring and biosurveillance. We propose a graphical tool that can reveal the distribution of an outcome by time and age simultaneously.We introduce and demonstrate multi-panel (MP) graphs applied in four different settings: U.S. national influenza-associated and salmonellosis-associated hospitalizations among the older adult population (≥65 years old), 1991-2004; confirmed salmonellosis cases reported to the Massachusetts Department of Public Health for the general population, 2004-2005; and asthma-associated hospital visits for children aged 0-18 at Milwaukee Children's Hospital of Wisconsin, 1997-2006. We illustrate trends and anomalies that otherwise would be obscured by traditional visualization techniques such as case pyramids and time-series plots.MP graphs can weave together two vital dynamics--temporality and demographics--that play important roles in the distribution and spread of diseases, making these graphs a powerful tool for public health and disease biosurveillance efforts